Final answer:
The question is about using a hypothesis test to determine if an auto manufacturer's fleet meets a fuel economy standard. A t-test would compare the sample mean of 34.6 mpg to the policy requirement of 35.5 mpg to see if there's statistical evidence that the fleet does not meet the standard at the 5 percent level.
Step-by-step explanation:
The question posed involves determining whether an auto manufacturer's fleet fuel economy meets the required average of 35.5 miles per gallon (mpg) as per the 2016 policy at the 5 percent significance level, using a sample mean of 34.6 mpg, with a given standard deviation of 10.3 mpg for the sample and known standard deviation of 7.6 mpg for the population.
To answer the question, one would execute a hypothesis test, presumably a one-sample t-test, given the sample standard deviation differs from the population standard deviation. The null hypothesis (H0) would assert that the true mean fuel economy is at least 35.5 mpg, while the alternative hypothesis (H1) would claim it is less than 35.5 mpg. Using the provided sample data (sample mean, sample size, and sample standard deviation), as well as the population standard deviation, statistical software or formulas would be used to calculate the t-test statistic and corresponding p-value.
If the p-value were less than the significance level of 0.05, the null hypothesis would be rejected, implying that there is statistical evidence that the fleet does not meet the required fuel economy standards. Conversely, if the p-value were greater than the significance level, the null hypothesis would not be rejected, indicating no statistical evidence that the fleet fails to meet the standards.